Estimating a neutral reference for electroencephalographic recordings: the importance of using a high-density montage and a realistic head model

Quanying Liu,Marc Baechinger,Onno Van Der Groen,Nicole Wenderoth,Joshua H Balsters,Dante Mantini

doi:10.1088/1741-2560/12/5/056012

Abstract

Objective. In electroencephalography (EEG) measurements, the signal of each recording electrode is contrasted with a reference electrode or a combination of electrodes. The estimation of a neutral reference is a long-standing issue in EEG data analysis, which has motivated the proposal of different re-referencing methods, among which linked-mastoid re-referencing (LMR), average re-referencing (AR) and reference electrode standardization technique (REST). In this study we quantitatively assessed the extent to which the use of a high-density montage and a realistic head model can impact on the optimal estimation of a neutral reference for EEG recordings. Approach. Using simulated recordings generated by projecting specific source activity over the sensors, we assessed to what extent AR, REST and LMR may distort the scalp topography. We examined the impact electrode coverage has on AR and REST, and how accurate the REST reconstruction is for realistic and less realistic (three-layer and single-layer spherical) head models, and with possible uncertainty in the electrode positions. We assessed LMR, AR and REST also in the presence of typical EEG artifacts that are mixed in the recordings. Finally, we applied them to real EEG data collected in a target detection experiment to corroborate our findings on simulated data. Main results. Both AR and REST have relatively low reconstruction errors compared to LMR, and that REST is less sensitive than AR and LMR to artifacts mixed in the EEG data. For both AR and REST, high electrode density yields low re-referencing reconstruction errors. A realistic head model is critical for REST, leading to a more accurate estimate of a neutral reference compared to spherical head models. With a low-density montage, REST shows a more reliable reconstruction than AR either with a realistic or a three-layer spherical head model. Conversely, with a high-density montage AR yields better results unless precise information on electrode positions is available. Significance. Our study is the first to quantitatively assess the performance of EEG re-referencing techniques in relation to the use of a high-density montage and a realistic head model. We hope our study will help researchers in the choice of the most effective re-referencing approach for their EEG studies.

Highlights

Electroencephalography (EEG) is a non-invasive approach of measuring brain activity at high temporal resolution using electrodes placed on the subject’s scalp
Both average re-referencing (AR) and reference electrode standardization technique (REST) have relatively low reconstruction errors compared to linked-mastoid re-referencing (LMR), and that REST is less sensitive than AR and LMR to artifacts mixed in the EEG data
A realistic head model is critical for REST, leading to a more accurate estimate of a neutral reference compared to spherical head models

Summary

Introduction

Electroencephalography (EEG) is a non-invasive approach of measuring brain activity at high temporal resolution using electrodes placed on the subject’s scalp This technique has been widely used to investigate such domains as perception, cognition, emotion and attention, given that it can provide great insights into the neural temporal dynamics underlying these processes (Carballogonzalez et al 1989, van der Lubbe et al 2000, Silberstein et al 2001, Porcaro et al 2009). One critical issue for EEG is to eliminate—or at least minimize—the effects of residual neuronal activity in the physical reference by re-referencing the data (Kayser and Tenke 2010) This can be done by estimating the signal in a virtual reference, typically combining information from multiple electrodes, and subtracting it from all recordings

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